We present PartNet: a consistent, large-scale dataset of 3D objects annotated with fine-
grained, instance-level, and hierarchical 3D part information. Our dataset consists of …

Three-dimensional (3-D) meshes have been used more and more in industrial, medical and
entertainment applications during the last decade. Many researchers, from both the …

This paper surveys mesh segmentation techniques and algorithms, with a focus on part‐
based segmentation, that is, segmentation that divides a mesh (featuring a 3D object) into …

Most attempts to represent 3D shapes for deep learning have focused on volumetric grids,
multi-view images and point clouds. In this paper we look at the most popular representation …

In this paper, we present a novel approach for 3D dental model segmentation via deep
Convolutional Neural Networks (CNNs). Traditional geometry-based methods tend to …

This paper describes a benchmark for evaluation of 3D mesh segmentation salgorithms. The
benchmark comprises a data set with 4,300 manually generated segmentations for 380 …

This paper presents a data-driven approach to simultaneous segmentation and labeling of
parts in 3D meshes. An objective function is formulated as a Conditional Random Field …

3D printing technology is rapidly maturing and becoming ubiquitous. One of the remaining
obstacles to wide-scale adoption is that the object to be printed must fit into the working …

We present a review of the state of the art of segmentation and partitioning techniques of
boundary meshes. Recently, these have become a part of many mesh and object …

Shape analysis plays a pivotal role in a large number of applications, ranging from
traditional geometry processing to more recent 3D content management. In this scenario …